A typical goal of signal processing is to improve the quality and the interpretability of captured or stored images. Infrared or even visible images are candidates for quality improvement when they contain areas having unsatisfactory contrast and/or brightness levels. Changing contrast and/or brightness levels over the whole image does not typically help because only unsatisfactory image areas should be processed so as to keep an amount of signal processing time to a minimum, thereby avoiding tying-up processing resources.
Several approaches or methods have been used to improve contrast and brightness in captured images, and in some of them the improvement turned out to be destructive as a significant amount of desired information ended up being removed from the processed images.
One conventional approach relies on a method to improve the overall image contrast of the processed digital images through the application of a tone scale function, constructed by a mathematical formula that relies on several control parameters. However, this application of the tone scale function amplifies the noise of the resultant processed digital image.
Another conventional approach uses histogram equalization which attempts to improve contrast on the captured or stored images by making the histogram more uniform. This equalization approach redistributes the intensity distributions based on a statistical process. A histogram equalized image brings out additional details that may have been in shadows or overexposed. However, one drawback of the histogram equalization is that some light or dark areas of the images may become saturated, thereby causing some difficulties in seeing details in those areas.
Still another conventional approach for contrast enhancement uses a local area contrast enhancement which pulls details out of bright and dark image areas. However, this local enhancement approach requires that the images be windowed or tiled, thereby increasing the number of operations or amount of processing per pixel.
Therefore, there is a need to remedy the problems noted above and others previously experienced for enhancing contrast and brightness in captured or stored images while minimizing loss of desired information, noise and processing time and resources.